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Abstract. Assessing impacts of climate change on hydrologic systemsis critical for developing adaptation and mitigation strategies for waterresource management, risk control, and ecosystem conservation practices. Suchassessments are commonly accomplished using outputs from a hydrologic modelforced with future precipitation and temperature projections. The algorithmsused for the hydrologic model components (e.g., runoff generation) canintroduce significant uncertainties into the simulated hydrologic variables.Here, a modeling framework was developed that integrates multiple runoffgeneration algorithms with a routing model and associated parameteroptimizations. This framework is able to identify uncertainties from bothhydrologic model components and climate forcings as well as associatedparameterization. Three fundamentally different runoff generationapproaches, runoff coefficient method (RCM, conceptual), variableinfiltration capacity (VIC, physically based, infiltration excess), andsimple-TOPMODEL (STP, physically based, saturation excess), were coupledwith the Hillslope River Routing model to simulate surface/subsurface runoffand streamflow. A case study conducted in Santa Barbara County, California,reveals increased surface runoff in February and March but decreasedrunoff in other months, a delayed (3 d, median) and shortened (6 d,median) wet season, and increased daily discharge especially for theextremes (e.g., 100-year flood discharge, Q100). The Bayesian modelaveraging analysis indicates that the probability of such an increase can be up to85 %. For projected changes in runoff and discharge, general circulationmodels (GCMs) and emission scenariosmore »